Ultrasound Nerve Segmentation using YOLO

TITLE	Ultrasound Nerve Segmentation using YOLO
ABSTRACT	Ultrasonic neural division is a medical activity undertaken to diagnose nerve block procedures and schedule operations. Manual segmentation is labour-intensive, highly subjective and error-prone due to the complicated structure of nerves, ultrasound interference, and lack of contrast and complexity. Manual segmentation has a number of limitations but the emergence of deep learning has made fully automatic segmentation methods possible. Advances made in deep-learning architectures, and specifically U-Net and U-Net++, which can utilize skip-nested connections, have improved feature learning. YOLO architecture also allows for real-time object detection increasing clinical usage, minimizing manual workloads, improving accuracy, and maximum reliability of identifying nerves.
AUTHOR	Prajwal Singh G, Dr Sunitha G P
PUBLICATION DATE	2025-08-26 11:15:02
VOLUME	13
ISSUE	3
DOI	10.15662/IJMSERH.2025.1303055
PDF	pdf/2025/7/55_Ultrasound Nerve Segmentation using YOLO.pdf
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